In this case study we look at how the Rosalind Franklin Institute deployed SenseAI to dramatically speed up and reduce the fluence for their 4D STEM electron microscopy.
Rosalind Franklin Institute speeds up 4D STEM with SenseAI
“We have been truly impressed by the speed of the imaging we can now do, with no loss of image fidelity. As we explore the possibilities further, we are excited to use this to advance our research even further, even quicker.”
Professor Angus Kirkland, Science Director at the Franklin Rosalind Institute
he Rosalind Franklin Institute is a leading UK research institute, dedicated to developing new technologies for life science. These insights speed up the discovery of new medicines and diagnostics, and tackle important health research challenges.
Some of the technologies in the Franklin’s advanced imaging are pushing the boundaries of electron microscopy techniques such as 4D STEM, to generate ever-more powerful ways to understand life science and relevant materials research.
Inevitably, as techniques become more powerful, more beam energy is required as well as more data processing. These high fluences can cause sample damage, and the data processing rates can increase exponentially.
The SenseAI software has made ‘sub-sampling’ truly fast and practical for the first time, meaning that fluences are 10% of the original dosages, and data rates can be up to 10x faster facilitating real-time video for 4D STEM.
The images included on this document show live 4D-STEM with virtual image inpainting enabled by SenseAI. This technique enables real time viewing of 4D-STEM data during both “Survey” and “Acquisition” modes. These techniques bring 4D-STEM imaging up to the same framerates as typical STEM acquisition and allows the seamless transition of 2D techniques to 4D.
Using SenseAI, the Rosalind Franklin Institute was able to dramatically speed up, and reduce the fluence for 4D STEM electron microscopy. The system was deployed on a JEOL GrandArm microscope using Quantum Detectors’ Merlin camera and scan engine. Further research is planned with papers to be published.
